Doctoral Program in Information Science And Technology

24 Pages·2012·0.78 MB·English

Doctoral Program in
Information Science
And Technology

Plan of Study 2011/2012
Course Syllabi

FIRST SEMESTER ..................................................................................................... 2
1. RESEARCH METHODS .................................................................................. 2
2. ADVANCED TOPICS ON ARTIFICIAL INTELLIGENCE ........................... 5
3. ADVANCED TOPICS ON COMMUNICATIONS ......................................... 7
4. BIOSIGNALS ANALYSIS AND PROCESSING ............................................ 9
5. DEPENDABILITY OF COMPUTER SYSTEMS .......................................... 10
6. SOFTWARE REUSE AND DESIGN PATTERNS ........................................ 12
7. STATISTICS ................................................................................................... 13
SECOND SEMESTER .............................................................................................. 14
1. ADVANCED TOPICS ON COGNITIVE MODELING ................................ 14
2. CONNECTIVITY AND PATTERNS RECOGNITION................................ 17
3. ONLINE LEARNING IN INTELLIGENT SYSTEMS ................................. 19
4. ADVANCED TOPICS ON DATA PROCESSING AND ANALYSIS......... 21

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Course Specifications
FIRST SEMESTER

1. RESEARCH METHODS

Professors:
Luís Paquete ([email protected])
Karen Bennett
Luís Macedo

Description

The goal of this course is to introduce the students to principles of empirical research based
on quantitative methods as well as to improve their research communication skills, both
orally and in writing. The course is split into two modules: Quantitative Methods (QM) and
Scientific Communication (SC). Each module is individually assessed (35%). At the end of the
two modules, the students will participate in a joint workshop where they have to present
and discuss a state-of-the-art review.

Scientific Communication Module

Aims:
This course aims to develop students’ skills in scientific communication, oral and written,
and will include both active and passive components. The focus will be on achieving clarity,
concision, coherence/cohesion and an appropriate style in specific academic/scientific text
types.

Course Content:
Analysis of the structure and language of different academic text types; planning and
drafting; writing scientific discourse; preparation and delivery of oral presentations; effective
reading.

Teaching Methods:
This course is taught as a seminar and will be student-oriented. This means that formal
presentations by the teacher will be kept to a minimum, and instead students will be
involved in task-based group activities, discussions and exercises. 2 written assignments will
be set but they are considered optional (that is to say, they will only affect the final
assessment positively, not negatively).

Assessment:
50% continuous assessment, 50% written assignment

Materials:
2
Material to be used in class will be posted on line before the lesson for students to
download and print.

Bibliography:
There are literally hundreds of manuals available to provide guidance in different aspects of
academic writing. These may be easily purchased on internet bookshops. The following are
available in the Department library:

Bailey, S. Academic Writing: A Handbook for International Students. London & New York:
Routledge. 2006.

Breach, M. Dissertation Writing for Engineers and Scientists. New Jersey: Prentice Hall. 2008.

Lester, J.D & Lester, J. Writing Research Papers: A Complete Guide. New York & London:
Longman. 2004.

Penrose, A.M & Katz, S.B. Writing in the Sciences: Exploring Conventions of

Scientific Discourse. London & New York: Longman, 2009.

Syllabus:

Lesson 1: Effective reading/textual organization/summarizing
- introduction to extensive reading techniques (skimming, scanning)
- textual analysis: deriving a plan from a written text
- using that plan to write a summary of the original article

Lesson 2: The grammar of scientific discourse
- complex noun phrases
- impersonal structures

Lesson 3: Abstracts
- analysis of different kinds of abstract
- cohesion and coherence (signposting devices, linkers etc)

Lesson 4: Oral presentations
- planning a short oral presentation
- focus on delivery (rhythm, posture, voice projection, stress, intonation, etc)

Lesson 5: Final Assessment
- planning and writing a short argumentative text

Quantitative Methods Module

Aims:
The goal of this course is to introduce the students to a wide range of tools and techniques
that will help them to conduct sound empirical and quantitative research. It will cover topics
of exploratory data analysis, inferential statistics, and experimental design. Special emphasis
will be given to techniques that allow a comprehensive interpretation of data, generalization
from sampled data and sound ways of designing experiments.
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Course Content:
Activities: Exploratory data analysis, inferential statistics and experimental design. Text
types: research articles.

Teaching Methods:
This course is mainly taught as a seminar with formal presentations by the teachers.
Discussions about particular case-studies will be considered.

Assessment:
Each student will critically review a paper that contains an experimental analysis.

Materials:
Material to be used in class will be posted on line before the lesson for students to
download and print.

Bibliography:
Any book that covers topics of inferential statistics and experimental design are appropriate
for this course. The following list is just indicative of some updated books in the field.

Hinkelmann, K. and Kempthorne, O., Design and Analysis of Experiments. I and II, (2nd ed.).
Wiley, 2008.

Sheldon, R., Probability and Statistics for Engineers and Scientists, Academic Press, 2009

Lilja, D., Measuring Computer Performance: A Practitioner's Guide, Cambridge University
Press, 2005.

Cohen, P., Empirical Methods for Artificial Intelligence, MIT Press, 1995

Syllabus:

Lesson 1: Metrics and Measurements
- Characteristics of good metrics
- Computer system metric
- Time measurement in computer systems
- Case study: experimental algorithms

Lesson 2: Graphics and Exploratory Data Analysis
- Classical Data Analysis vs. Exploratory Data Analysis
- Box plot
- Histogram
- Run chart
- Lag plot
- Scatter plot
- Star plot
- Q-Q plot
- Others

Lesson 3: Inferential Statistics
- Introduction to Inferential Statistics
- Confidence Interval
- Hypothesis Testing
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Lesson 4: Design of Experiments
- The strategy of experimentation
- Principles and terminology in Design of Experiments
- Guidelines for planning, conducting and analyzing experiments

Lesson 5: Design of Experiments
- Practical examples and exercises

2. ADVANCED TOPICS ON ARTIFICIAL INTELLIGENCE

Professors:
Luis Macedo ([email protected])
Paulo Gomes ([email protected])
Pedro Quaresma ([email protected] )

Course Summary:
This course intends to provide the student the context for learning a set of advanced
Artificial Intelligence research topics in depth, with a solid theoretical contextualization and
corresponding empirical support. It is organized in a set of Options Modules with a workload
of 2 ECTS each, covering a wide area of advanced topics. Each individual learning plan will
comprise 2 of those modules and will be defined by the student’s supervisor, in accordance
to the specific needs of the student’s PhD plan, in collaboration with the student and the
course’s coordinator.

Contents:
Module 1 - Natural Language Processing
Introduction to Natural Language Processing
Morphological Analysis
Syntactic Analysis
Semantic Analysis
Applications

Module 2 - Knowledge Discovery
Data Mining
Text Mining
Web Mining

Module 3 - Intelligent Systems for Knowledge Management
Introduction to Knowledge Management
Knowledge Representation and Indexing
Knowledge Search and Retrieval
Knowledge Reuse and Sharing
Knowledge Extraction and Learning

Module 4 - Ontologies
Introduction to Ontologies
Ontology Development Methodology
Tools for Ontology Creation
Issues in Ontology Design
Ontology Application

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Module 5 - Semantic Web
Introduction to the Semantic Web
Tools for Ontology Creation and Management
Search, Retrieval and Integration
Distributed Ontologies
Semantic Web Applications

Module 6 - Planning
Classical Planning
Hierarchical task network planning
Decision-theoretic planning

Module 7 - Affective Computing and Consciousness
Emotion and motivation
Artificial affective agents
Consciousness

Module 8 - Exploration of Unknown Environments and Map Construction
Environment types
Maps: metric, topologic and hybrid
Exploration strategies
Multi-agent exploration techniques: collaboration and coordination; communication.

Evaluation Model:
A: Synthesis or State-of-the-Art: 50% - about chosen module 1
B: Case study or Lab work: 50% - about chosen module 2

Selected Bibliography:
see http://classes.dei.uc.pt/course/view.php?id=25

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3. ADVANCED TOPICS ON COMMUNICATIONS
Professors:
Fernando Boavida ([email protected] )
Edmundo Monteiro ([email protected])
Jorge Sá Silva ([email protected] )
Marília Curado ([email protected] )
Paulo Simões (psimõ[email protected] )

Summary:
To discuss and explore several networking research topics centered in Quality of Service
(QoS) and Mobility and Management. In what concerns QoS, topics of interest include
routing, robustness, resilience, trust and security. Relating mobility and wireless, the
addressed topics include host and network mobility, 3G and 4G systems, pervasiveness and
wireless sensor networks.

Contents:
1. Introduction: current networking needs, motivations and trends 1.1. The role of
networking technologies in the evolution of communications 1.2. The role applications in the
evolution of communications 1.3. Quality-of-service-aware networking 1.4. Ubiquitous
computing 1.5. Trends in Internet evolution 2. Mobility 2.1. Introduction 2.2. Fundamentals
and evolution of wireless networks 2.3. Micro-mobility 2.4. Mobile IP 2.5. Mobile networks
2.6. Research issues in mobility

Enduring Principles:
The Internet is being subject to intense stress and change. On one side, new requirements
and applications are developed every day, putting current technologies under strain. On the
other, recent research efforts address challenging issues and promise considerable change in
the years to come. In this scenario, three main areas arise as extremely important, requiring
attention now and in the foreseeable future: quality of service, mobility and management.
The first of these areas will determine how the Internet will respond to the requirements of
emerging and future applications. The second area will shape the solutions for ubiquitous
and seamless connectivity for both users and networks. The third area will largely influence
the way the network runs, evolves and adapts to the operational environment, in a more or
less autonomic way. This course will provide an informed and state-of-the-art view on each
of these areas.

Evaluation Model:
Evaluation of a paper describing and discussing the state of the art about one of the topics
addressed in the course.

Selected Bibliography:
I. F. Akyildiz, W. Su , Y. Sankarasubramaniam, E. Cayirci, Wireless sensor networks: a survey,
Computer Networks: The International Journal of Computer and Telecommunications
Networking, v.38 n.4, p.393-422, 15 March 2002.

Liu, T., Liao, W.: On routing in multichannel wireless mesh networks: Challenges and
solutions. Network, IEEE 22 (2008) 13–18.

J. W. Hui and D. E. Culler, “IP is dead, long live IP for wireless sensor networks,” in SenSys
’08: Proceedings of the 6th ACM conference on Embedded network sensor systems. New
York, NY, USA: ACM, 2008, pp. 15–28.

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W. Srinivasan and K.-C. Chua, “Trade-offs between mobility and density for coverage in
wireless sensor networks,” MobiCom ’07: Proceedings of the 13th annual ACM international
conference on Mobile computing and networking. New York, USA: ACM, 2007, pp. 39–50.

K. Liu, M. Li, Y. Liu, M. Li, Z. Guo and F. Hong, "Passive Diagnosis for wireless Sensor
Networks," in SenSys ’08: Proceedings of the 6th ACM conference on Embedded Network
Sensor Systems, Raleigh, NC, USA, 2008.

I. Akyildiz, X. Wang, “Cross-Layer Design in Wireless Mesh Networks”, IEEE TRANSACTIONS
ON VEHICULAR TECHNOLOGY, VOL. 57, NO. 2, MARCH 2008.

M. Yannuzzi, X. Masip-Bruin, S. Sánchez-López, J. Domingo-Pascual, A. Fonte, M. Curado, and
E. Monteiro, “On the Advantages of Cooperative and Social Smart Route Control”, in
Proceedings of International Conference on Computer Communications and Networks
(ICCCN’2006), IEEE Communication Society, Arlington, Virginia, USA, October 9 - 11, 2006.

U. Engelke and H. Zepernick, “Perceptual-based Quality Metrics for Image and Video
Services: A Survey”, In Proceedings of IEEE Conference Next Generation Internet Networks,
Trondheim, Norway, May 2007.

For each topic to be addressed in the course a list of additional relevant papers will be
provided to the students.

Selected Bibiography:
The basic bibliography to be used in the course is listed below:

802.11 Wireless Networks, Second Edition
Mathew S. Gast,
Ref: O’Reilly & Associates, Inc., 2005.

High-Speed Networks and Internets – Performance and Quality of Service, 2nd Edition
William Stallings,
Ref: Prentice Hall, 2002

Quality of Service Routing
Piet Van Mieghem, Fernando Kuipers, T. Korkmaz, M. Krunz, Marília Curado, Edmundo
Monteiro, Xavier Masip-Bruin, José Sole-Pareta, Jordi Domingo-Pascal, “Quality of Service
Routing”, Chapter 3, in Quality of Future Internet Services, Michel Smirnoff, Jim Roberts and
Jon Crowcroft (Eds.)"
Ref: LNCS, Vol. 2856, Springer-Verlag, 2003.

Wireless Internet Telecommunications
K. Daniel Wong,
Ref: Artech House, 2005. ISBN 1-58053-711-1.

Wireless IP and Building the Mobile Internet
Sudhir Dixit, Ramjee Prasad (editors),
Ref: Artech House, 2003. ISBN 1-58053-354-X

Wireless Networks
P. Nicopolitidis, M. S. Obaidat, G. I. Papadimitriou, A. S. Pomportsis,
Ref: John Wiley & Sons Ltd., 2003. ISBN 0-470-84529-5
Wireless Sensor Networks
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C.S. Raghavendra et al. (Ed.),
Ref: Kluwer Academic Publishers, 2004. ISBN 1-4020-7883-8.

4. BIOSIGNALS ANALYSIS AND PROCESSING

Professors:
Jorge Henriques ([email protected])
Paulo de Carvalho ([email protected] )
Summary:
Biosignal Analysis and Processing involves extracting useful information
from biological signals for diagnostics and therapeutics purposes.

Contents: 1. Characterizing of biosignals and features extraction
- Application of time domain, frequency domain and time-frequency domain
- Analytic methods

2. Classifiers (review)
- Application of soft computing methodologies

3. Case studies

ECG signal analysis and processing
- Segmentation
- Arrhythmias detections

EEG signal analysis and processing
- Sleep stage classification
- Apnea detection

Enduring Principles:
The enduring principle of the course is to provide the students with a deep understanding of
the trade-offs and appropriateness of analysis and processing techniques, employed to
developed clinical decision support systems.

Evaluation Model:
40%: State-of-the-art overview in a specific subject
60%: Implementation work

Selected Bibliography:
State-of the art papers (to be defined).

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5. DEPENDABILITY OF COMPUTER SYSTEMS

Professors:
Raul Barbosa ([email protected] )
Mário Zenha Rela ([email protected])
Luis Moura e Silva ([email protected])

Summary:
The goal of this course is to provide the PhD student with advanced background knowledge
on System's Dependability by doing analysis and discussion of selected readings of the
literature. This activity will be fundamental for those students that plan to do research in this
or related areas.

Contents:
Initial Readings:
- "How (and How Not) to Write a Good Systems Paper"
- "Efficient Reading of Papers Science Technology"

CLASS 1: The Basics of Dependability
Selected readings:
- "Basic Concepts and Taxonomy of Dependable and Secure Computing"
- "Software Fault-Tolerance"
- "Lessons from Giant-Scale Services"
- "Towards Systematic Design of Fault-Tolerant Systems"

CLASS 2: CAUSES OF FAILURES
Selected readings:
- "Causes of failures in Web-Applications"
- "Why do computers stop and what can be done about it?"
- "Why Internet services fail and what can be done about it?"
- "Studying and using failure-data from large-scale internet services"

CLASS 3: AVAILABILITY
Selected readings:
- "Blueprints for High Availability" (Book Wiley and Sons: 2nd Edition)
- Chapter 5: 20 Key High-Availability Design Principles
- Chapter 15: Local Clustering and Failover,
- Chapter 16: Failover Management and Issues,
- Chapter 17: Failover Configurations
- "Improving Systems Availability"

CLASS 4: RELIABILITY
Selected readings:
- "A Study of Reliability of Internet Sites"
- "When does fast recovery trump high reliability"

CLASS 5: FAILURE DETECTION
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